The goal of this program is to create a clinical system for non-invasively recording EMG motor unit signals. This system will use Blind Source Deconvolution (BSD) signal processing techniques to collect these signals with surface electrode arrays, rather than needle electrodes that must be inserted and manipulated by highly trained clinicians. This system will improve the speed, cost, and patient comfort of common clinical evaluations that require motor unit recording (such as Carpal Tunnel and diabetic neuropathy), and potentially improve the accuracy and diagnostic sensitivity of surface nerve conduction studies. In addition, by reducing the need for EMG needle insertion and manipulation, this system will enable new remote monitoring and telehealth diagnostic capabilities for common diseases such as Carpal Tunnel Syndrome and diabetic neuropathy. In Phase I, we will verify the ability of Blind Source Deconvolution (BSD) to extract motor unit signals from surface EMG of the thenar muscles using a 256-channel, thin-film EMG electrode array and offline data analysis. In Phase II, we will develop a compact, disposable surface electrode array and a miniaturized data acquisition system with software that implements the BSD algorithms in real-time. This final clinical system will provide audio and video displays of the recordings, quantitative measures regarding the number, size and shape of extracted motor units, and distribution information for the unit conduction velocities. [unreadable] [unreadable]